To date, many vibration-based sensing modalities have relied upon monitoring small shifts in the natural frequency of a system to detect structural changes (e.g. in mass or stiffness), which are attributable to the chemical, biological, or other types of phenomenon that are being measured. Often, this approach carries significant signal processing expense, due to the presence of electronics such as precision phase locked loops, when high sensitivities are required.
Microelectromechanical systems (MEMS) based sensing is an important area of transducer development and has been so for the past several decades. This importance stems from its potential to provide low-cost, scalable, and sensitive sensor alternatives based upon a wide variety of modalities. Resonant mode sensing is common in MEMS devices and is founded on correlating changes in the resonant behavior of structures and devices to identifiable parameter changes. Traditional methods in this area rely on linear or pseudo-linear sensing, which, in turn, rely on a shift in resonant frequencies of a vibrating structure to detect changes, either in the device structure or its surroundings. These methods have been successfully used to detect a number of chemical and other small masses (picograms and smaller in many cases), and have also found use in applications such as atomic force microscopy (AFM). It is important to note, however, that performing sensing in the linear mode with high sensitivity requires careful system design and may require significant cost or complexity to implement. It may require phase-locked loops, lock-in amplifiers, or other specialized equipment to perform the measurements and yield high sensitivity in frequency shift measurement.
Bifurcation-based mass sensing, on the other hand, is an approach to mass sensing that relies upon nonlinear behavior to produce large changes in amplitude when a mass change threshold is exceeded. Previous successful sensing efforts using bifurcation-based sensing have achieved high sensitivity albeit with the tradeoff being that the methods usually do not measure mass in a quantifiable manner aside from a certain threshold being exceeded.
Many microscale resonator devices capable of operating in a nonlinear regime commonly exhibit classical Duffing-like frequency responses. These devices can exhibit multiple coexisting steady-state solutions (stable and unstable), saddle-node bifurcations, and hysteretic behavior. A potential disadvantage to the state of the art in bifurcation-based sensing in microscale devices is the fact that in many cases the systems must be driven with magnitudes of excitation that may damage the device (18 V peak-to-peak excitation was required, where the device has a nominal breakdown voltage of 10 V). It is also worth noting that it may be possible to compensate for this by redesigning devices specifically for bifurcation-based sensing, but this may not be economical or practical for all applications (higher drive amplitudes require higher power circuitry to function, and this reduces applicability for battery powered, low power, mobile sensing).
One approach to tackling the aforementioned issue is to use feedback to produce a bifurcation at lower drive amplitudes. Prior work in this area has a bistable system structure rather than that of a Duffing resonator, but also had the disadvantage of the vibration actuation being separate (non-collocated). Likewise, nonlinear feedback methods have been suggested for use in MEMS devices in the past, but generally for reduction or elimination of nonlinear behavior. Notably the majority of this work has been performed either in simulation or on relatively low-frequency, macro-scale analogs of MEMS systems.
Most small-scale resonant sensor designs utilize linear phenomena for sensing. Specifically, they utilize chemomechanically-induced changes in mass or stiffness, to induce a change in resonant frequency and thus signal a detection event. These systems have proven utility in laboratory settings, but have not transferred to real-world, portable sensing applications, due to hardware constraints and the fixed sensitivity of the devices.
Thus a need exists for a sensors that can sense mass, stiffness, and chemical or biological substances which are more sensitive and tunable. It also desirable to have such sensing approaches allow for significantly reduced costs, improved reliability and enhanced robustness. It is further desirable to have sensing approaches that eliminate the need for customized mechanical/electrical designs.
According to a first embodiment of the present disclosure, a sensing device is provided including: a sensor having a functional surface layer located to interact with a material to be sensed, the sensor having an output that produces a signal responsive one or more of inertia, stiffness, acceleration, pressure, radiation, chemical compounds, and biological compounds; and further including electronics including: an input coupled to the sensor to receive a first signal therefrom; and a non-linearity provider that applies one or more non-linear operations to the input signal to generate a non-linear second signal.
According to another embodiment of the present disclosure, a method of generating a non-linear sensor response is provided including: obtaining a first signal from a sensor having a functional surface layer located to interact with a material to be sensed, the sensor having an output that produces a signal responsive one or more of inertia, stiffness, acceleration, pressure, radiation, chemical compounds, and biological compounds; and applying one or more non-linear electrical operations, including a first operation, to the first signal to generate a non-linear second signal.
According to another embodiment of the present disclosure, a computer readable media having non-transitory instructions thereon is provided, that when interpreted by a processor cause the processor to: obtain a first signal from a sensor having a functional surface layer located to interact with a material to be sensed, the sensor having an output that produces a signal responsive one or more of inertia, stiffness, acceleration, pressure, radiation, chemical compounds, and biological compounds; and apply one or more non-linear electrical operations, including a first operation, to the first signal to generate a non-linear second signal.